Product pages.
One ecommerce model.
Across your sources.
Turn each Capture into a consistent product record with normalized taxonomy, attributes, options, identifiers, commerce data, review aggregates, and signals.
Enrich gives inconsistent product pages one queryable structure without discarding their source evidence. It produces one self-contained Item per Capture. When the job also requires cross-store identity, Extend adds beta Product, Variant, Listing, and Offer relationships as a separate downstream stage.
catalog imports
Start with your catalog, then compare it to the market.
If you already have product data, you do not need to crawl your own storefront first. Import the catalog file directly. Extralt converts valid rows into Captures, then sends them through the same Enrich, Extend, and Explore path as open-web data.
That gives you one dataset for first-party catalog records, competitor listings, prices, availability, and product matches. Your catalog becomes the reference point for the broader market you extract around it.
product data enrichment · three angles
Inspect products, categories, and brands through one model.
Extend · beta
Add cross-store relationships when the workflow needs them
Extend reads enriched Items and connects equivalent product families and exact configurations across the stores in your dataset. It uses identifier evidence, normalized product content, selected options, and similarity signals while keeping source Listings and matching coverage inspectable.
Variants stay exact. A shoe with four colors and twelve sizes can produce up to 48 configurations when the source exposes those combinations. Listings point to Variants, and Variants roll up to Products for like-for-like price and assortment analysis.
- Cross-seller resolutionWhen the evidence supports a match, the same exact Variant across sellers connects to one canonical Variant. Listings keep their source-specific details.
- Variant-level granularityColor, size, width, material, and other selected options stay on the Variant. A 4 color by 12 size shoe can be 48 variants, not one page-level record.
- Identifier unificationGTIN can provide exact evidence when brand and option conflicts are absent. MPN remains supporting evidence. Source SKU ids stay on Listings.
- Multi-language normalizationA French and a German listing of the same product end up with comparable English fields. The original-language text stays on the record for display.
deliverables
What you get
Output
Enriched Items
One page-grain Item per Capture
Coverage
Validated sources
Public pages and imported catalogs
Languages
Original + English
Source text kept alongside translation
Access
Views · API · SQL
Plus JSON or Parquet Capture exports
why extralt
Built for catalogs that come from everywhere.
One model across sources
Validated marketplace, retailer, DTC, and catalog inputs use the same ecommerce structure. Source-dependent values remain present only when exposed.
Customer-facing data, not a separate feed
Enrich structures what was captured from the customer-facing page while preserving the source URL, original content, and lineage behind the Item.
Taxonomy and attributes included
Enrich maps categories, category-specific attributes, and product signals into a consistent structure instead of leaving that schema work to every downstream project.
The page-grain enriched output comes from Enrich, the second stage of the Extralt pipeline. Captures from Extract become page-grain Items with taxonomy, attributes, options, commerce data, review aggregates, signals, and English normalization. When those Items need to resolve across sellers, beta Extend publishes the comparable Product, Variant, Listing, and Offer relationships.
who it's for
For teams whose data comes from many sources and needs to look like one.
- Catalog & merchandising teamsNormalize supplier feeds, marketplace listings, and scraped competitor data into one shape. Stop maintaining mapping rules per source.
- Market intelligence analystsSlice the observed dataset by brand, attributes, and price tier. See assortment shape without rebuilding mappings for every source.
- Product & data teams building on topSearch, recommendations, and agent-facing APIs that need product structure they can reason about. Inherit the schema instead of building it.
Frequently asked questions
Turn your next Capture into structured product data.
Enrich costs one credit per Capture processed. Add Extend when you need matched Products, Variants, Listings, and Offers.